Who Needs Neural Networks? The Generative Prowess of State Transition Models

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Contrary to popular belief, not all generative models for AI require deep learning, neural networks, and the large language models (LLMs) many consider synonymous with Generative AI, if not AI itself. Traditional non-statistical AI approaches, which consists of rules-based systems and are typified by symbolic reasoning, are just as viable, if not more so, for certain generative model use cases.

In fact, there are generative models that involve both non-statistical rules and probabilistic, or statistical, measures. According to Franz CEO Jans…



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Who Needs Neural Networks? The Generative Prowess of State Transition Models


Contrary to popular belief, not all generative models for AI require deep learning, neural networks, and the large language models (LLMs) many consider synonymous with Generative AI, if not AI itself. Traditional non-statistical AI approaches, which consists of rules-based systems and are typified by symbolic reasoning, are just as viable, if not more so, for certain generative model use cases.

In fact, there are generative models that involve both non-statistical rules and probabilistic, or statistical, measures. According to Franz CEO Jans…



Source link

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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